Price J H, Hunter E A, Gough D A
Department of Bioengineering, University of California, San Diego, La Jolla 92093-0412, USA. jhprice.ucsd.edu
Cytometry. 1996 Dec 1;25(4):303-16. doi: 10.1002/(SICI)1097-0320(19961201)25:4<303::AID-CYTO1>3.0.CO;2-E.
A method for accurate, real-time image segmentation is needed for the development of a fully automated image cytometer that combines the speed and case-of-use of flow cytometry with the detailed morphometry of imaging. Object intensity variation and inherent optical blur make real-time segmentation challenging. The best spatial finite impulse response (FIR) filter, implemented as a convolution, was tested for sharpening edges and creating the required contrast. The filter and threshold segmentation steps were treated as a two-category linear classifier. Best 3 x 3 through 25 x 25 filters were designed utilizing the perceptron criterion and nonlinear least squares, and tested on ten montage images of a combined 1,070 manually segmented DAPI stained cell nuclei. The resulting image contrast, or class separation, led to simple automatic thresholding via the histogram intermodal minimum. Image segmentation accuracy began to plateau at 7 x 7 filters and did not increase above 15 x 15. Little loss in accuracy occurred with application to the images not used for design. This segmentation method provides a systematic, fast and accurate means of creating binary object maps useful for subsequent measurement, processing and cell classification.
开发一种将流式细胞术的速度和易用性与成像的详细形态测量学相结合的全自动图像细胞仪，需要一种准确的实时图像分割方法。目标强度变化和固有的光学模糊使得实时分割具有挑战性。作为卷积实现的最佳空间有限脉冲响应（FIR）滤波器经过测试，用于锐化边缘并创建所需的对比度。滤波器和阈值分割步骤被视为两类线性分类器。利用感知器准则和非线性最小二乘法设计了最佳的3×3至25×25滤波器，并在1070个手动分割的DAPI染色细胞核的组合蒙太奇图像上进行了测试。所得的图像对比度或类别分离通过直方图双峰最小值实现简单的自动阈值处理。图像分割精度在7×7滤波器时开始趋于平稳，在15×15以上没有提高。应用于未用于设计的图像时，精度损失很小。这种分割方法提供了一种系统、快速且准确的方法来创建用于后续测量、处理和细胞分类的二值化目标图。
